☆ 3.8 Article

Analysis of data consistency identifies measurement abnormality in Howells' craniometric test data set

AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY (2022)

A Unifying Review of Deep and Shallow Anomaly Detection

Lukas Ruff et al.

Summary: Deep learning approaches have significantly enhanced anomaly detection performance on complex data sets, sparking a renewed interest in the field. Various new methods have been introduced, including those based on generative models, one-class classification, and reconstruction. It is crucial to bring these methods together and explore the underlying principles and connections between classic and novel approaches for future research and development in anomaly detection.

PROCEEDINGS OF THE IEEE (2021)

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Review Chemistry, Multidisciplinary

A Review of Machine Learning and Deep Learning Techniques for Anomaly Detection in IoT Data

Redhwan Al-amri et al.

Summary: The paper discusses the importance and challenges of anomaly detection in IoT data processing, summarizing the various aspects of issues and core challenges in IoT data processing, including data characteristics, anomaly types, learning modes, window models, and more.

APPLIED SCIENCES-BASEL (2021)

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Article Medicine, Legal